[Tutor] Regarding help in python algorithm

Fri Jul 5 02:25:49 EDT 2019

Hi,
I am a student at an university. Currently I was working on an algorithm
using python. It is based on scheduling the teachers to their nearest
venues. And at the venues there can be atmost 400 teachers and these are to
be divided into the Batches of 40 i.e. ten batches. All the batches will
have teachers having same group number assigned to them. and al the batches
should get only the two days from the working days in the month.
This is only the last part of the complete algorithm. I am sending the
files associated to it and the code that I have made till now. Please help
me in making it as I need it urgently.

Thanks in advance.
Regards

Suhit
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import math
import csv
import pdb
import pandas as pd 
import numpy as np 
from math import radians, sin, cos, acos

def distanceCalculator(latitude1,longitude1,latitude2,longitude2):
        slat = radians(latitude1)
        slon = radians(longitude1)
        elat = radians(latitude2)
        elon = radians(longitude2)
        dist = 6371.01 * acos(sin(slat)*sin(elat) + cos(slat)*cos(elat)*cos(slon - elon))
        return dist

#df = pd.read_csv("venueData.csv",header=None)

df2 = pd.read_csv("mtdata.csv",header=None)

df2.columns = ['name','location','latitude','longitude','subject']

df = pd.read_csv("venueData.csv",header=None)

df.columns=['name','latitude','longitude']

#df2 = pd.read_csv("mtdata.csv",header=None)

#df2.columns = ['name','location','latitude','longitude','subject']

teacher = pd.read_csv("teachers.csv")

teacher['Latitude'] = teacher['Latitude'].apply(lambda x: x.rstrip(",") if type(x)  == str else x )

teacher['Longitude'] = teacher['Longitude'].apply(lambda x: x.rstrip(",") if type(x)  == str else x )

listEmpty = []

dictionaryTeacher = {}

for i,ex in teacher.iterrows():

    lat1 = ex['Latitude']
    lon1 = ex['Longitude']

    Id = i 

    for b,c in df.iterrows():

        lat2 = c['latitude']
        lon2 = c['longitude']

        nameVen = c['name']

        listEmpty.append((distanceCalculator(float(lat1),float(lon1),float(lat2),float(lon2)),Id,b))        

    demian = []    

    listEmpty.sort()   

    demian = listEmpty[0]

    dictionaryTeacher[ex['Name']] = demian

    listEmpty = []

    demian = []

DataTeacher = pd.DataFrame(columns=['Teacher','Distance','Venue','Eng','Hindi','Maths'])

number = 3 

for ex in dictionaryTeacher:

    DataTeacher= DataTeacher.append({'Teacher':ex,'Distance':dictionaryTeacher[ex][0],'Venue':df.loc[dictionaryTeacher[ex][2]]['name'],'Eng':teacher.loc[dictionaryTeacher[ex][1]]['Eng'],'Hindi':teacher.loc[dictionaryTeacher[ex][1]]['Hindi'],'Maths':teacher.loc[dictionaryTeacher[ex][1]]['Maths']},ignore_index=True)

days = pd.read_csv("days.csv")

days.columns = ['January', 'January:Days', 'February', 'Feburary:Days', 'March',
       'March:Days', 'April', 'April:Days', 'May', 'May:Days', 'June',
       'June:Days', 'July', 'July:Days', 'August', 'August:Days',
       'September', 'September:Days', 'October', 'October:Days', 'November',
       'November:Days', 'December', 'December:Days']

df.columns=['name','latitude','longitude']

df['name'] = df['name'].apply(lambda x: x.rstrip())

df2['name'] =df2['name'].apply(lambda x: x.rstrip())

venue = {}

for i,k in enumerate(df['name']):

    if (k not in venue):

        venue[k] = {'January': 0 ,'February':0 , 'March': 0 , 'April':0, 'May':0,'June ':0 ,'July':0 , 'August':0,'September':0,'October':0,'November':0,'December':0}

teacher = {}

for i,k in enumerate(df2['name']):

    if (k not in teacher):

        teacher[k] = {'January': 0 ,'February':0 , 'March': 0 , 'April':0, 'May':0,'June ':0 ,'July':0 , 'August':0,'September':0,'October':0,'November':0,'December':0}
dictionary = {}

liste = []

for i,ex in df2.iterrows():

    nameT = ex['name']
    lat1  = ex['latitude']
    lon1  = ex['longitude']
    sub   = ex['subject'] 
    Id = i 

    for b , x in df.iterrows():

        nameM = x['name']
        lat2  = x['latitude']
        lon2  = x['longitude']
        id2 = b

        liste.append((distanceCalculator(lat1,lon1,lat2,lon2),i,id2))

    liste.sort()

    dictionary[ex['name']] = liste[0:3]

    liste = []

Data = pd.DataFrame(columns=['Trainer','Venue','Distance','Subjects','Location'])

for ex in dictionary:

    for i , k in enumerate(dictionary[ex]):

        Data = Data.append({'Trainer':ex ,'Venue': df.loc[dictionary[ex][i][2]]['name'],'Distance': dictionary[ex][i][0],'Subjects':df2.loc[dictionary[ex][i][1]]['subject'],'Location':df2.loc[dictionary[ex][i][1]]['location']},ignore_index=True)

Data['Month'] = -1

for i,ex in Data.iterrows():

    Train = ex['Trainer']
    Venue = ex['Venue']

    for ex in teacher[Train]:

        if(teacher[Train][ex]==0):

            if(venue[Venue][ex] == 0):

                teacher[Train][ex] = 1
                venue[Venue][ex] = 1

                Data.loc[i,"Month"] = ex
                break
strings = " "

for ex in days[days["January"][:].str.contains("Tue")]['January'].index:

    strings += ","+ str(ex)

strings = strings.rstrip(",")

strings = strings.lstrip()

Data['Month'] = Data['Month'].apply(lambda x : x.rstrip())

listeDays = []

Cal = 0 

num = 0 

strings = ""

for i,ex in Data.iterrows():

    ay = ex['Month']

    indexOfDays = days[days[ay][:].str.contains("Mon") |  days[ay][:].str.contains("Tue") | days[ay][:].str.contains("Wed") | days[ay][:].str.contains("Thu") | days[ay][:].str.contains("Fri")][ay].index

    for ex in days[days[ay][:].str.contains("Mon") |  days[ay][:].str.contains("Tue") | days[ay][:].str.contains("Wed") | days[ay][:].str.contains("Thu") | days[ay][:].str.contains("Fri")][ay]:

        num = indexOfDays[Cal]

        num +=1

        Cal +=1

        strings += str(num) + "," + ex + ","

    Data.loc[i,"Days"] = strings
    num = 0 
    Cal = 0 

    strings = ""

Data['Month'] = Data['Month'].apply(lambda x: x.rstrip())

Data['Days'] = Data['Days'].apply(lambda x : x.replace("\n",","))

DfSub = pd.read_csv("backupMasterTrainers.csv")

copyDfSub = DfSub

ab = DfSub.sample(n=1)

ab.columns = ['Name',"Location","Latitude","Longitude","Subject"]

Id = ""

VenID = 0 

newName = ""

dist = ""

VenLat =""

VenLot =""

newLat = ""

newLon = ""

newSub = ""

newLoc = ""

for i,ex in Data.iterrows():

    name = ex['Trainer']
    month = ex['Month']
    lecture = ex['Subjects']    

    print(name,"Do you want to give ",lecture,"in this month :",month)
    answer = input("For Yes : Y For No N") 

    if answer == 'Y' or answer == 'y':

        pass

    elif answer == 'N' or answer =='n':
        ab = copyDfSub.sample(n=1)
        ab.columns = ['Name',"Location","Latitude","Longitude","Subject"]

        Id = ab.index[0]

        newName = ab.loc[Id,"Name"]

        newLat = ab.loc[Id,"Latitude"]

        newLon = ab.loc[Id,"Longitude"]

        newSub = ab.loc[Id,"Subject"]

        newLoc = ab.loc[Id,"Location"]

        VenueName = ex['Venue']

        for z,b in df.iterrows():

            if(VenueName in b['name']):

                VenID = z 

        VenLat = df['latitude'][z]

        VenLon = df['longitude'][z]

        dist = distanceCalculator(newLat,newLon,VenLat,VenLon)

        Data.loc[i,"Trainer"] = newName

        Data.loc[i,"Distance"] = dist

        Data.loc[i,"Subjects"] = newSub

        Data.loc[i,"Location"] = newLoc

        copyDfSub.drop(Id,inplace=True)
        copyDfSub.reset_index(drop=True,inplace=True)

df5 = pd.merge(Data,DataTeacher,on="Venue",how='inner')
df5.to_csv("trainingData.csv")